It is well accepted that the biological activity of organisms, organ systems and cells produces measurable electromagnetic activity. At one end of the spectrum is the high frequency activity (alternating current) of neural tissue and at the other end is the steady state (direct current) activity hypothesized to indicate abnormal cell or tissue growth. For example, medical applications of high frequency (AC) electromagnetic field measurements are manifest in electroencephalographic and electrocardiographic devices. More recently, direct current (DC) fields have been studied as a method of cancer diagnosis. For example, U.S. Pat. No. 4,328,809 to B. H. Hirschowitz and U.S. Pat. No. 4,955,383 to M. L. Faupel contemplate devices and methods for measuring and analyzing DC electropotentials for disease diagnosis or screening. In these inventions, information in the extremely low frequency alternating current (AC) band is filtered out through averaging a multiplicity of signals taken over time. Higher frequency information is filtered out using active or passive digital or analog filters. Other manifestations of this approach have been articulated in U.S. Pat. No. 4,407,300 to Davis and U.S. Pat. No. 4,557,273 to Stoller et al. Davis, for example, discloses the diagnosis of cancer by measuring the electromotive forces generated between two electrodes applied to a subject.
If measurements are taken from several test points on the body, as contemplated in the aforementioned Hirschowitz and Faupel patents, as well as in U.S. Pat. No. 4,416,288 to Freeman and U.S. Pat. No. 4,486,835 to Bai, comparisons of the averaged DC potentials from the plurality of test points may be of particular interest. Furthermore, the averaged DC voltages may be further analyzed by discriminant function analysis, as disclosed in particular by the aforementioned Faupel patent.
These disease diagnosis techniques using only DC electropotentials sacrifice information (e.g., low frequency AC information) for ease of processing afforded by a singular filtered and/or averaged measurement from each test site on the body. Unfortunately, this loss of information may compromise diagnostic accuracy of many disease states. For example, public disclosure of clinical studies involving analysis of DC potentials indicate that while there may be some degree of diagnostic accuracy for large (palpable) cancers, the same approach appears to be relatively ineffective for small (nonpalpable) cancers. Since it is well recognized that early detection of disease states offers the best chance for patient survival, improvement in this capacity over previous disclosures is indicated. Moreover, previous pattern recognition techniques used for analysis of electropotential fields may be overly simplistic in that they do not take into account the complexities of biological systems and their disease states. To this point, it is known that the biology and concomitant electromagnetic activity of malignant tumors, for example, change over time. In order to maximize effectiveness, novel diagnostic and screening techniques based on the measurement of electromagnetic fields must take into account both the short term changes in electrical activity (e.g., extremely low frequency AC fields) as well as the longer term changes which occur as a disease state progresses. Failure to do so results in major deficiencies leading to diagnostic inaccuracy.
For example, changes in extremely low frequency alternating current (ELFAC) may differ for malignant vs. benign tumors, because the gating mechanisms controlling ion transport across the epithelial tissue layer can differ between the diseased and nondiseased condition, or other reasons. It is known that malignant epithelial cells lose, to varying degrees, the ability to transport ions and fluids across the epithelial layer. It is this low frequency time-varying phenomena which is lost by restricting analysis of electrical signals to an averaged and/or filtered DC component.
In addition, changes over the longer term indicate that the electromagnetic behavior of small malignant tumors may be very different from that of larger tumors, which have been found to produce redox potentials as a result of the degradation of tissue within the core of the tumor. Another factor is smaller tumors may be more metabolically active and therefore more relatively depolarized than larger tumors.
It follows then that analysis of important electromagnetic changes must take these factors into account in order to maximize diagnosis and screening of disease states.